Project initialization
Start a project state with an empty constitution. The README says plan and feature can also do this automatically if needed.
FluencyLoop is an AI-assisted development workflow for Claude Code and Codex that helps teams capture decisions, document feature work, and assemble reviewer-ready summaries. It is built around branch-local documentation and a private knowledge profile that adjusts teaching depth across projects.
FluencyLoop is an AI-assisted development workflow for Claude Code and Codex that aims to produce understanding alongside code. It helps teams initialize a project, plan larger work, build features in slices, and assemble reviewer-ready summaries while keeping documentation tied to the actual branch and implementation history.
The repository describes a loop where each feature produces a documented design, captures real decisions and rejected alternatives, and updates a short project constitution as repeatable engineering stances emerge. FluencyLoop also keeps a private per-developer knowledge profile so explanations can stay concise on familiar topics and more detailed where needed, without committing that profile to the project.
Start a project state with an empty constitution. The README says plan and feature can also do this automatically if needed.
Break a large initiative into feature-sized tasks before implementation when the work is too large for a single feature.
Create a feature branch, build in slices, teach each real decision, and journal the work as it happens.
Assemble branch sessions and decisions into a reviewer-facing pull request view.
Track rationale for each decision, including what was chosen, why it was chosen, what was rejected, and how it relates to the constitution and design.
Maintain a private per-developer calibration profile so the workflow can adjust teaching depth across projects without committing that profile to the repo.
Use FluencyLoop when a feature needs implementation and documentation to stay aligned. The workflow keeps design notes, decision records, and review material attached to the branch that produced them.
Use the planning stage when an initiative is too large to build as a single feature. The tool breaks the work into feature-sized tasks before the team starts implementation.
Use the review stage to turn a branch's sessions and decisions into a reviewer-facing pull request summary. This is useful when reviewers need the rationale behind the code, not only the diff.
Use backfill when work was already merged without FluencyLoop. The repository says the backfill command can reconstruct and verify design and decisions after the fact.
Use the per-developer knowledge profile when different contributors need different levels of explanation. The workflow adapts teaching depth based on demonstrated familiarity.
It is a developer workflow tool for teams using Claude Code or Codex. The repository describes FluencyLoop as a way to initialize a project, plan larger work, build a feature in slices, and assemble a review-ready summary.
The README says the practical path for normal-sized work is init → feature → review. For larger initiatives, you can run plan first and then repeat feature → review for each task.
FluencyLoop outputs a living constitution, plans, Mermaid design diagrams, feature sessions, review summaries, and a private per-developer knowledge base that is not committed to the project.
The repository says FluencyLoop requires Claude Code or Codex, git, and either Bash on macOS/Linux/Git Bash/WSL or PowerShell on native Windows.
The project is hosted in a public GitHub repository. The pricing page for GitHub shows free public repositories, but the repository itself does not provide separate product pricing details.
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